Express diagnosis
We review one process, identify losses and deliver priorities and a clear next step.
Request diagnosis Process engineering · Montevideo, Uruguay
Practical AI for businesses in Uruguay
Improve inquiries, quotes and repetitive tasks with automation and applied AI.
Write on WhatsAppReal problems AI can solve today
I lose inquiries on WhatsApp
Quoting takes too long
My clients don't understand the process
I have repetitive documents and tasks
I don't know where to start with AI
What you can hire
Three distinct stages. Start with a diagnosis and continue only when the result justifies the next step.
Working pilot
We build a limited version of the new process and test it with controlled cases.
Discuss a pilotIntegration
After validating the pilot, we connect the required channels and systems and support adoption.
Ask about integrationProcesses we can improve
These are illustrative examples. Open a card to see the problem, a possible process, the tool and how it would be measured.
- What is lost
- Replies arrive late, prospect data is incomplete, and follow-up depends on one person's memory.
- What changes
- Structured WhatsApp intake with automatic classification.
- What we build
- Prospect record, visit scheduling and status-based follow-up.
- How we measure
- First-response time and unattended inquiries.
- What is lost
- Technicians ask for the same details again, quotes are delayed and ownership is unclear.
- What changes
- Conversational intake with summary and suggested priority.
- What we build
- Issue summary, assigned owner and next actions.
- How we measure
- Classification time, rework and quote turnaround.
- What is lost
- Clients do not know what is missing and the team checks the same information several times.
- What changes
- Automatic checklist by procedure type with alerts.
- What we build
- Missing-item control, next-step guidance and notifications.
- How we measure
- Repeated reviews, incomplete files and resolution time.
- What is lost
- Manuals, logs and procedures are separated; finding an answer can stop a task.
- What changes
- Local knowledge base with RAG search.
- What we build
- Document assistance and incident logging.
- How we measure
- Search time, interruptions and answer consistency.
- What is lost
- Front desk staff repeat answers, maintenance notices arrive late and guests lack status visibility.
- What changes
- Inquiry assistant and internal tasks with assigned owners.
- What we build
- Task creation, reminders, statuses and escalation.
- How we measure
- Front-desk load, response time and overdue tasks.
- What is lost
- Information jumps between spreadsheets, email and messaging, creating errors and duplicate work.
- What changes
- Single data capture with validation rules.
- What we build
- Automatic reminders and an exception dashboard.
- How we measure
- Manual hours, errors and request-to-close time.
One routine first, not a total transformation
The first conversation does not attempt to redesign the whole company. We find a repetitive task with impact that can be compared before and after.
01 We pick one important repetitive task
We map how work arrives, who decides, what information is missing and where it waits.
02 We measure time, errors and losses
We define the flow, rules and where AI helps. Important decisions remain human.
03 We build a limited pilot
We build a controlled version and use real cases before connecting more systems.
04 We compare the actual result
We compare time, errors and follow-up. If it creates value, we integrate or expand it.
05 We scale only with proven impact
Without measured impact we don't advance. With clear impact, the next step is already designed.
Clear process Gradual implementation Practical AI Human + automation
See how a case could work
Interactive demo with fictional data: intake, classification, owner and next action.
DEMOWater near electrical outlet — Apt 4B
Incoming message
AI Analysis
Structured case
Assignment
Result
WhatsApp — María Rodríguez
Impact calculator
Losses first, then the solution
Use your own operating data. The potential resource is not a guaranteed profit.
Estimated total lossUYU 0per month
Unfollowed opportunitiesUYU 0
Preventable overcostsUYU 0
Potentially recoverable resourceUYU 0
- Implementation and automationUYU 0
- Capacity returned to sales or serviceUYU 0
- Adjustment and contingency marginUYU 0
If nothing changes
The same losses repeat every month.
per yearUYU 0
If tested with a pilot
A measured process can recover part of the resource.
Potential resource / per yearUYU 0
Tools and lines of work
Working demo
Explore NODO HUB NODO HUB by AI-Gnatev
An interactive prototype showing how inquiries, owners, statuses and next actions can be organized.
Specialized service
See service Real Estate AI
A proposed process for inquiry filtering, visits, documents and real-estate follow-up.
Engineering concept
See project Edge AI Mini-PC
A portable agent with local knowledge, document privacy and field connectivity.
Research
See research Risk-centric model
A conceptual architecture connecting events, constraints, decisions and operational risk.
First step
Bring one routine that currently depends on copying, remembering or chasing information.
We review it, choose a metric and decide whether it needs an express diagnosis, a pilot, or no automation at all.